Antenna Season Report Notebook¶

Josh Dillon, Last Revised January 2022

This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.

In [1]:
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
In [2]:
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
In [3]:
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "34"
csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
In [4]:
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))

Antenna 34 Report

In [5]:
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
In [6]:
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 49 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_
Found 47 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
In [7]:
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'

Load relevant info from summary CSVs¶

In [8]:
this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
            antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
        else:
            antnum = int(row['Ant'])
        if antnum != int(antenna):
            continue
        
        if np.issubdtype(type(row['Node']), np.integer):
            row['Node'] = str(row['Node'])
        if type(row['Node']) == str and row['Node'].isnumeric():
            row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break
In [9]:
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])

Table 1: Per-Night RTP Summary Info For This Atenna¶

This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.

In [10]:
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))

Antenna 34, Node N06:

Out[10]:
JDs A Priori Status Auto Metrics Flags Dead Fraction in Ant Metrics (Jee) Dead Fraction in Ant Metrics (Jnn) Crossed Fraction in Ant Metrics Flag Fraction Before Redcal Flagged By Redcal chi^2 Fraction ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score Average Dead Ant Metric (Jee) Average Dead Ant Metric (Jnn) Average Crossed Ant Metric Median chi^2 Per Antenna (Jee) Median chi^2 Per Antenna (Jnn)
2459864 not_connected 100.00% 100.00% 0.00% 0.00% - - 25.439825 5.421480 8.202844 11.016412 8.239873 1.019112 3.243979 -0.072523 0.0402 0.6515 0.5464 nan nan
2459863 not_connected 100.00% 100.00% 0.00% 0.00% - - 15.497850 2.039172 2.643168 -0.252139 2.993942 3.802171 1.337655 -0.831860 0.0409 0.6450 0.5400 nan nan
2459862 not_connected 100.00% 100.00% 0.00% 0.00% - - 15.339473 2.954082 8.905305 13.356398 12.482944 2.685019 1.017191 -0.780173 0.0455 0.6795 0.5273 nan nan
2459861 not_connected 100.00% 100.00% 0.00% 0.00% - - 11.830891 1.122095 2.886264 -1.894759 2.546711 3.270494 1.024776 -0.354363 0.0397 0.6577 0.5068 nan nan
2459860 not_connected 100.00% 100.00% 0.00% 0.00% - - 12.830820 1.959494 8.468623 7.718041 14.681356 2.254181 1.304324 -0.805962 0.0408 0.6493 0.5552 nan nan
2459859 not_connected 100.00% 100.00% 0.00% 0.00% - - 10.788176 0.894657 3.347653 -2.390551 2.240509 2.951603 0.337352 -0.741215 0.0434 0.6553 0.5461 nan nan
2459858 not_connected 100.00% 100.00% 0.00% 0.00% 100.00% 0.00% 11.729288 0.814840 3.372854 -2.894663 2.287258 8.237116 1.007570 1.526418 0.0416 0.6597 0.5473 1.241931 2.881606
2459857 not_connected 100.00% 100.00% 100.00% 0.00% - - 5.029107 0.585648 0.250278 1.362252 0.734939 3.721368 3.302402 0.708987 0.0290 0.0289 0.0006 nan nan
2459856 not_connected 100.00% 100.00% 0.00% 0.00% 100.00% 0.00% 17.278313 3.031357 8.287908 6.437786 6.652525 2.840174 2.034517 -0.859082 0.0440 0.6735 0.5689 1.244955 2.562242
2459855 not_connected 100.00% 100.00% 0.00% 0.00% 100.00% 0.00% 18.202161 3.546594 7.784330 8.139510 2.684589 8.430062 0.507626 -0.923274 0.0436 0.6853 0.5829 1.220033 3.047257
2459854 not_connected 100.00% 100.00% 0.00% 0.00% 100.00% 0.00% 18.230710 3.150288 5.606733 6.605160 3.839472 3.606942 2.815106 0.432287 0.0442 0.7206 0.6015 1.231065 3.017055
2459853 not_connected 100.00% 100.00% 0.00% 0.00% 100.00% 0.00% 15.115139 2.708840 8.419716 8.423114 7.037320 4.055470 2.456752 0.055527 0.0447 0.6602 0.5507 1.242437 3.383687
2459852 not_connected 100.00% 100.00% 0.00% 0.00% 100.00% 0.00% 13.817689 4.602917 9.199763 10.414589 15.603567 3.644895 16.692812 8.429692 0.0416 0.8093 0.6659 1.214775 5.442199
2459851 not_connected 100.00% 90.23% 0.00% 0.00% 100.00% 0.00% 12.017169 4.397950 8.546470 9.720896 21.468027 10.339538 12.387225 7.504056 0.0988 0.7138 0.4942 0.866643 2.079185
2459850 not_connected 100.00% 100.00% 0.00% 0.00% 100.00% 0.00% 14.495922 3.153455 7.424956 7.830817 10.308146 4.237785 5.394209 2.879895 0.0484 0.7301 0.5719 1.265949 3.091004
2459849 not_connected 100.00% 100.00% 0.00% 0.00% 100.00% 0.00% 16.757320 2.806751 16.268505 15.011370 7.128088 4.315881 2.966135 -0.358714 0.0428 0.7206 0.5744 1.270871 3.494749
2459848 not_connected 100.00% 100.00% 0.00% 0.00% 100.00% 0.00% 15.496630 2.959010 8.518637 11.830365 14.319080 3.782307 1.121389 -0.811380 0.0430 0.7271 0.5836 1.253355 3.210068
2459847 not_connected 100.00% 100.00% 0.00% 0.00% 100.00% 0.00% 17.713985 3.075747 7.683540 12.145552 21.779563 6.416233 0.036489 -0.836231 0.0376 0.6601 0.5313 1.156511 3.019124
2459846 not_connected 100.00% 100.00% 0.00% 0.00% 100.00% 0.00% 27.416778 6.596305 14.777133 10.385713 21.659479 1.862991 3.587379 -0.443634 0.0369 0.6607 0.5103 0.812346 1.397902
2459845 not_connected 100.00% 100.00% 0.00% 0.00% 100.00% 0.00% 19.540275 3.705230 12.631284 14.952011 10.103377 3.448940 0.583008 -1.311327 0.0484 0.7333 0.5825 0.000000 0.000000
2459844 not_connected 100.00% 100.00% 100.00% 0.00% - - 10.471518 3.143226 51.369139 55.946271 0.349979 4.944669 2.372725 1.034953 0.0282 0.0286 0.0009 nan nan
2459843 not_connected 100.00% 100.00% 0.66% 0.00% 100.00% 0.00% 20.020080 6.360883 6.017662 15.026662 64.263762 4.610992 0.189582 -2.710582 0.0426 0.7389 0.5775 0.000000 0.000000
2459842 not_connected 100.00% 100.00% 0.00% 0.00% 100.00% 0.00% 11.945509 1.569544 3.582351 -0.164784 -0.105533 -1.720372 0.425890 -2.246716 0.0487 0.6095 0.4343 1.263186 3.372820
2459841 not_connected 100.00% 100.00% 0.00% 0.00% - - 10.599907 44.902973 32.519816 122.025821 51.116090 97.172070 22.255647 8.216420 0.0466 0.7384 0.3532 nan nan

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

In [11]:
htmls_to_display = []
for am_html in auto_metric_htmls:
    html_to_display = ''
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line:
            htmls_to_display.append(html_to_display)
            break

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.

In [12]:
for i, html_to_display in enumerate(htmls_to_display):
    if i == 100:
        break
    display(HTML(html_to_display))

Antenna 34: 2459864

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
34 N06 not_connected ee Shape 25.439825 5.421480 25.439825 11.016412 8.202844 1.019112 8.239873 -0.072523 3.243979

Antenna 34: 2459863

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
34 N06 not_connected ee Shape 15.497850 15.497850 2.039172 2.643168 -0.252139 2.993942 3.802171 1.337655 -0.831860

Antenna 34: 2459862

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
34 N06 not_connected ee Shape 15.339473 15.339473 2.954082 8.905305 13.356398 12.482944 2.685019 1.017191 -0.780173

Antenna 34: 2459861

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
34 N06 not_connected ee Shape 11.830891 1.122095 11.830891 -1.894759 2.886264 3.270494 2.546711 -0.354363 1.024776

Antenna 34: 2459860

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
34 N06 not_connected ee Temporal Variability 14.681356 12.830820 1.959494 8.468623 7.718041 14.681356 2.254181 1.304324 -0.805962

Antenna 34: 2459859

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
34 N06 not_connected ee Shape 10.788176 10.788176 0.894657 3.347653 -2.390551 2.240509 2.951603 0.337352 -0.741215

Antenna 34: 2459858

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
34 N06 not_connected ee Shape 11.729288 0.814840 11.729288 -2.894663 3.372854 8.237116 2.287258 1.526418 1.007570

Antenna 34: 2459857

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
34 N06 not_connected ee Shape 5.029107 0.585648 5.029107 1.362252 0.250278 3.721368 0.734939 0.708987 3.302402

Antenna 34: 2459856

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
34 N06 not_connected ee Shape 17.278313 17.278313 3.031357 8.287908 6.437786 6.652525 2.840174 2.034517 -0.859082

Antenna 34: 2459855

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
34 N06 not_connected ee Shape 18.202161 3.546594 18.202161 8.139510 7.784330 8.430062 2.684589 -0.923274 0.507626

Antenna 34: 2459854

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
34 N06 not_connected ee Shape 18.230710 3.150288 18.230710 6.605160 5.606733 3.606942 3.839472 0.432287 2.815106

Antenna 34: 2459853

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
34 N06 not_connected ee Shape 15.115139 2.708840 15.115139 8.423114 8.419716 4.055470 7.037320 0.055527 2.456752

Antenna 34: 2459852

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
34 N06 not_connected ee Temporal Discontinuties 16.692812 13.817689 4.602917 9.199763 10.414589 15.603567 3.644895 16.692812 8.429692

Antenna 34: 2459851

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
34 N06 not_connected ee Temporal Variability 21.468027 12.017169 4.397950 8.546470 9.720896 21.468027 10.339538 12.387225 7.504056

Antenna 34: 2459850

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
34 N06 not_connected ee Shape 14.495922 14.495922 3.153455 7.424956 7.830817 10.308146 4.237785 5.394209 2.879895

Antenna 34: 2459849

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
34 N06 not_connected ee Shape 16.757320 16.757320 2.806751 16.268505 15.011370 7.128088 4.315881 2.966135 -0.358714

Antenna 34: 2459848

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
34 N06 not_connected ee Shape 15.496630 2.959010 15.496630 11.830365 8.518637 3.782307 14.319080 -0.811380 1.121389

Antenna 34: 2459847

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
34 N06 not_connected ee Temporal Variability 21.779563 3.075747 17.713985 12.145552 7.683540 6.416233 21.779563 -0.836231 0.036489

Antenna 34: 2459846

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
34 N06 not_connected ee Shape 27.416778 27.416778 6.596305 14.777133 10.385713 21.659479 1.862991 3.587379 -0.443634

Antenna 34: 2459845

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
34 N06 not_connected ee Shape 19.540275 3.705230 19.540275 14.952011 12.631284 3.448940 10.103377 -1.311327 0.583008

Antenna 34: 2459844

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
34 N06 not_connected nn Power 55.946271 10.471518 3.143226 51.369139 55.946271 0.349979 4.944669 2.372725 1.034953

Antenna 34: 2459843

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
34 N06 not_connected ee Temporal Variability 64.263762 6.360883 20.020080 15.026662 6.017662 4.610992 64.263762 -2.710582 0.189582

Antenna 34: 2459842

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
34 N06 not_connected ee Shape 11.945509 11.945509 1.569544 3.582351 -0.164784 -0.105533 -1.720372 0.425890 -2.246716

Antenna 34: 2459841

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
34 N06 not_connected nn Power 122.025821 10.599907 44.902973 32.519816 122.025821 51.116090 97.172070 22.255647 8.216420
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